Quick answer
Technology E&O responds when a client claims your software or service failed to perform. Integrating a third-party model does not move that exposure to the model vendor: your client contracted with you. The policy questions are whether AI-related work was disclosed and endorsed, whether the vendor's terms shift liability back to you, and whether your limits still match the contracts you signed.
The contract names you, not the model vendor
Most enterprise agreements warrant that your service will perform as described and will not infringe third-party rights. When a model returns a wrong answer, a biased result, or content that resembles someone else's protected work, the client's claim arrives at your company.
Model vendors typically disclaim warranties, cap liability, and require you to indemnify them for how you use the output. Read those terms before signing an enterprise contract that promises accuracy you cannot control.
Where tech E&O responds
- Failed performance. The client's process broke, output was wrong, or the integration did not deliver the promised result. This is the core professional services claim.
- Defense costs. Even weak claims require counsel, and defense usually outruns settlement.
- Subcontractor and vendor acts. Some forms cover work performed on your behalf. Confirm the wording, because a model vendor is not a subcontractor in the traditional sense.
- Not covered: your own lost revenue from an outage, regulatory fines, and anything excluded by an AI endorsement.
The AI exclusion problem
This is the fastest-moving wording in the technology E&O market. Several carriers now exclude or restrict claims arising from generative AI, model training, or automated decision-making, or require the work to be disclosed and endorsed.
Three outcomes are possible on a given form:
1. AI work is covered with no special wording.
2. AI work is covered only if disclosed and endorsed, with sublimits.
3. AI work is excluded outright.
Do not assume you are in the first category. Ask the carrier in writing how it treats model output errors, model training on client data, and claims alleging discriminatory or defamatory output.
Third-party model training and client data
If you fine-tune or train on client data, three exposures appear at once:
- Confidentiality. Client data used in training can breach a contract even when no breach occurs.
- Rights in output. Clients may claim ownership of models or outputs derived from their data.
- Regulatory. Sector rules on automated decisions can attach to your product.
Tech E&O may defend a contract claim about data use, but it does not pay regulatory penalties. Cyber liability covers breach response, not contract interpretation.
What to disclose on the application
- Which model providers you use and whether you call them through an API or host models yourself.
- Whether you train or fine-tune on customer data, and what the customer agreement says.
- Whether your product makes automated decisions affecting people (credit, hiring, pricing, eligibility).
- Whether contracts include accuracy warranties, service levels, or indemnities for third-party claims.
- Whether you carry cyber liability alongside tech E&O.
A disclosed AI operation with a documented review process prices better than an undisclosed one discovered at claim time.
Practical risk controls
1. Contract for what you control. Promise integration performance and support, not model accuracy.
2. Pass through vendor limits. Mirror the model vendor's disclaimers into your own terms where your client will accept them.
3. Human review where the output matters. Document the review step.
4. Log inputs and outputs. An audit trail shortens both investigation and defense.
5. Review limits against your largest contract. A $1M limit against a $5M enterprise agreement is a gap, not a rounding error.
Start with the technology E&O overview or request a technology quote.
General information about coverage structure, not a quote or a coverage opinion. Terms and exclusions are set by each carrier's policy form.